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Mastering Object-oriented Python

You're reading from   Mastering Object-oriented Python If you want to master object-oriented Python programming this book is a must-have. With 750 code samples and a relaxed tutorial, it's a seamless route to programming Python.

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Product type Paperback
Published in Apr 2014
Publisher Packt
ISBN-13 9781783280971
Length 634 pages
Edition Edition
Languages
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Author (1):
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Steven F. Lott Steven F. Lott
Author Profile Icon Steven F. Lott
Steven F. Lott
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Table of Contents (26) Chapters Close

Mastering Object-oriented Python
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Some Preliminaries
1. The __init__() Method FREE CHAPTER 2. Integrating Seamlessly with Python Basic Special Methods 3. Attribute Access, Properties, and Descriptors 4. The ABCs of Consistent Design 5. Using Callables and Contexts 6. Creating Containers and Collections 7. Creating Numbers 8. Decorators and Mixins – Cross-cutting Aspects 9. Serializing and Saving – JSON, YAML, Pickle, CSV, and XML 10. Storing and Retrieving Objects via Shelve 11. Storing and Retrieving Objects via SQLite 12. Transmitting and Sharing Objects 13. Configuration Files and Persistence 14. The Logging and Warning Modules 15. Designing for Testability 16. Coping With the Command Line 17. The Module and Package Design 18. Quality and Documentation Index

Chapter 4. The ABCs of Consistent Design

The Python Standard Library provides abstract base classes for a number of features of containers. It provides a consistent framework for the built-in container classes, such as list, map, and set.

Additionally, the library provides abstract base classes for numbers. We can use these classes to extend the suite of numeric classes available in Python.

We'll look in general at the abstract base classes in the collections.abc module. From there, we can focus on a few use cases that will be the subject of detailed examination in future chapters.

We have three design strategies: Wrap, Extend, and Invent. We'll look at the general concepts behind the various containers and collections that we might want to wrap or extend. Similarly, we'll look at the concepts behind the numbers that we might want to implement.

Our goal is to assure that our application classes integrate seamlessly with existing Python features. If we create a collection, for example, it's appropriate...

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